We demonstrate our proposed workflow using various ODE solvers and two ODE models, first with simulated and then with real data. In all experiments we use the dynamic HMC algorithm [1]}, [2]} implemented in Stan for MCMC sampling. We use initial leap frogThis refers to the step size of the MCMC sampler, and should not be confused with the step size of the ODE solver used to solve the modeled system. The lower initial value of 0.1 was observed to reduce some warmup problems compared to default 1.0. step size \(0.1\)  and otherwise default configuration, unless otherwise mentioned. In each experiment we run 4 independent MCMC chains for 4000 iterations and the first 2000 iterations are discarded as warmup. Code for reproducing the experiments is available at https://github.com/jtimonen/numapprox-is. Full experiment details are in Appendix .
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